A closer look at computer vision in investing

In a recent blog exploring the immediate implications of artificial intelligence (AI) and machine learning (ML) in asset management, I touched on how computer vision has risen as a significant

cognitive technological resource within the industry. This technology strives to emulate the human visual system, producing efficient recognition and high-level understanding of videos, images, and other visual mediums in an attempt to compile data and symbolic information. This data, in turn, can be referenced for a variety of reasons to “understand complex signals from visual content, including economic trends to emotion, intent, feelings, and desires.”

The finance industry — namely its investing branch — stands as one of several markets empowered or otherwise impacted by the rise of computer vision and AI. Computers are now able to absorb and analyze visual content faster and more accurately than ever before, and with a growing list of uses for this compilation of real-time data, implications for this technology in the financial sector are incredibly vast.

But what is computer vision, and how are its specific offerings enduringly relevant to modern investing? Here is a quick look at this intriguing branch of automated technology.

Finding trends

Thanks to advancements in computer vision technology, financial investors are now able to better identify economic market trends in real time. Fascinatingly, much of this information has been gathered via the analysis of satellite images. This content technically been available for years, but it has only just come into its own as a fruitful data mine thanks to concurrent growth in computer vision sophistication and data availability. As a result, investors have the ability to keep simultaneous tabs on key economic variables ranging from shipping ports to agricultural yields, building a stronger all-around knowledge of the global economy at large. By placing these responsibilities on the automated shoulders of computer vision, investors are able to stay connected to these vital trends while remaining free to focus on other key parts of their respective companies.

A bright future

Computer vision has already grown to be recognized as a cornerstone of modern AI, and as industry automatons continuously refine their ability to extract and efficiently dissect visual data, it is assumed that the financial world will collectively lean on it more to model environments based on geospatial economic data.

While other industries have been temporarily disrupted this technology’s rise to ubiquity, the finance industry appears poised to embrace it as an enabling force. Outside of key trend identification via image analysis, computer vision will smooth over lingering hindrances in user experience, quicken internal efficiencies across the board, and ultimately redefine investing workforces for the greater good of companies worldwide. There is still much to learn about computer vision’s potential, but at this point, its only restrictions appear to lie in the human imagination.